Function-Based Rhizosphere Assembly along a Gradient of Desiccation in the Former Aral Sea

ABSTRACT The desiccation of the Aral Sea represents one of the largest human-made environmental regional disasters. The salt- and toxin-enriched dried-out basin provides a natural laboratory for studying ecosystem functioning and rhizosphere assembly under extreme anthropogenic conditions. Here, we investigated the prokaryotic rhizosphere communities of the native pioneer plant Suaeda acuminata (C.A.Mey.) Moq. in comparison to bulk soil across a gradient of desiccation (5, 10, and 40 years) by metagenome and amplicon sequencing combined with quantitative PCR (qPCR) analyses. The rhizosphere effect was evident due to significantly higher bacterial abundances but less diversity in the rhizosphere compared to bulk soil. Interestingly, in the highest salinity (5 years of desiccation), rhizosphere functions were mainly provided by archaeal communities. Along the desiccation gradient, we observed a significant change in the rhizosphere microbiota, which was reflected by (i) a decreasing archaeon-bacterium ratio, (ii) replacement of halophilic archaea by specific plant-associated bacteria, i.e., Alphaproteobacteria and Actinobacteria, and (iii) an adaptation of specific, potentially plant-beneficial biosynthetic pathways. In general, both bacteria and archaea were found to be involved in carbon cycling and fixation, as well as methane and nitrogen metabolism. Analysis of metagenome-assembled genomes (MAGs) showed specific signatures for production of osmoprotectants, assimilatory nitrate reduction, and transport system induction. Our results provide evidence that rhizosphere assembly by cofiltering specific taxa with distinct traits is a mechanism which allows plants to thrive under extreme conditions. Overall, our findings highlight a function-based rhizosphere assembly, the importance of plant-microbe interactions in salinated soils, and their exploitation potential for ecosystem restoration approaches. IMPORTANCE The desertification of the Aral Sea basin in Uzbekistan and Kazakhstan represents one of the most serious anthropogenic environmental disasters of the last century. Since the 1960s, the world's fourth-largest inland body of water has been constantly shrinking, which has resulted in an extreme increase of salinity accompanied by accumulation of many hazardous and carcinogenic substances, as well as heavy metals, in the dried-out basin. Here, we investigated bacterial and archaeal communities in the rhizosphere of pioneer plants by combining classic molecular methods with amplicon sequencing as well as metagenomics for functional insights. By implementing a desiccation gradient, we observed (i) remarkable differences in the archaeon-bacterium ratio of plant rhizosphere samples, (ii) replacement of archaeal indicator taxa during succession, and (iii) the presence of specific, potentially plant-beneficial biosynthetic pathways in archaea present during the early stages. In addition, our results provide hitherto-undescribed insights into the functional redundancy between plant-associated archaea and bacteria.

In the manuscript "Function-based rhizosphere assembly along a gradient of desiccation in the former Aral Sea", as the authors indicated, these results confirm that along the desiccation gradient, a significant change in the rhizosphere microbiota were observed in the rhizosphere microbiota of native pioneer plants. The results provide evidence that rhizosphere assembly by cofiltering specific taxa with distinct traits is a mechanism, which allows plants to thrive under extreme conditions. Here are some suggestions about this manuscript. 1.Clearly explain the significant changes in the rhizosphere microbiota of native pioneer plants across a gradient of desiccation (5, 10, and 40 years) were obtained in the abstract. 2.Line 32-34, "The rhizosphere effect was shown by significantly higher abundances but less diversity in the rhizosphere compared to bulk soil in all samples." Do bacterial and archaeal communities have the same alteration trend? 3.Why bacterial and archaeal communities were investigated rather than fungal communities? 4.Line 113-115, "Although S. acuminata is not a classical pioneer plant, it fulfils this role under the specific extreme conditions in the Aral Sea basin.". Reference should be cited. 5.Line 126-128, "We collected bulk soil and rhizosphere samples (three biological replicates -approx. 5 g per biological replicate) of the plant Suaeda acuminata (C.A.Mey.) Moq. in the dried-out basin and near the west shoreline of the South Aral Sea". Overall, my concern is why Suaeda acuminata was select? 6.Line 296, delete an "in". 7.In legend of figure 1, (A), (B), (C) and (D) should be explained clearly. 8.In legends of figure 1 and 5, "High", "Medium" and "low" should be explained clearly.
Reviewer #2 (Comments for the Author): The manuscript mSystems00739-22 by Wicaksono and coauthors reports an investigation of the compositional and functional diversity and quantification of prokaryotes (bacteria and archaea) associated with the rhizosphere of native pioneer halophytic Suaeda acuminata along a desiccation gradient in the former Aral Sea. Metagenome and amplicon sequences approach, along with qPCR, were applied to 12 samples (9 rhizospheres and 3 soils) across three sites exposed to desiccation for 5, 10 and 40 years. Different bacterial microbiomes were found in the rhizosphere and soil, with different structures and assemblies among the sites, due to the combination of plant co-filtering and environmental conditions of sites (desiccation, salt concentration, toxin, etc.). Notably, along the desiccation gradient, the authors showed that the rhizosphere microbial communities had a decreasing archaea-bacteria ratio, a replacement of halophilic archaea by certain bacteria, and an adaptation of specific beneficial microbial functions, such as carbon cycling and fixation, methane and nitrogen metabolism, and production of osmoprotectants, which could support plants to thrive under extreme conditions. Overall, the manuscript is well written, the results are clearly presented, and the conclusions are well supported.
Below are some minor criticisms and my comments/suggestions: Line 33. Which pioneer plant? Maybe it can be specified from the beginning. Are all the collected plants the same species? Is this evaluated? Line 35. Why is the site with 5 years of desiccation considered the most extreme? Not really get this sentence. I suppose that at this site the salt concentration is the highest. I suggest reporting at least this info related to the three sites also in the abstract. Line 42. Are these MAGs coming only from the rhizosphere? Line 99-103. While Lin et al 2022 describe the overall trend of the rhizosphere microbiome in terms of composition/assembly and predicted function/trophic behaviours, a work recently published confirmed the predicted functionality by applying the metagenome approach (see 10.1038/s43705-022-00130-7). The authors showed that the root system represents a microbial density and competition hotspot ruled out by a dual selection process: to colonize the plant-associated niches microorganisms must (1) possess the capacity to improve the fitness and survival of the plant (plant selection of beneficial microbes, PGP bacteria) and be able (2) to compete successfully against other microorganisms (microbial competition). It will be interesting to explore if this competition is also present in salty/desiccation soils and how this occurs along the desiccation gradient. Lines 108-109. Among others, 10.1038/s41396-022-01238-3 showed how the autochthonous community in desert soil promotes the growth of plants, suggesting the potential of edaphic microbes and their ability to further colonize new plants and exert their beneficial services. I suggest better discussing the functional aspect of soil community and interaction with plants. Line 130. How did you collect 5 g of rhizosphere? How many plants were used for each replicate? Is this species the main abundance? How is it distributed along the desiccation gradient? Line 131. How was plant species identified during the sampling? Did you perform a molecular check on all samples collected to confirm they are the same species? Are the plants selected in the same phenological stage and have the same size? Could the latest be affected by salinity/desiccation? This is also an interesting point to be explored/discussed/tested. Lines 142-143. This passage is not clear. You added 20 ml of solution, but you stated that the resulting suspension was 2ml. Did you just collect a portion? Please clarify and add the range of soil used for DNA extraction (weighted after the centrifuge) so that readers have an idea. Lines 156-157. How were qPCR results normalized? Based on the taxonomy obtained the different copy numbers of 16S rRNA of bacterial and archaea communities could be retrieved across the three sites. Line 179. Why Silva 128? A more recent version (138) is available. Is the classifier trained with the primer used? Please specify how many chloroplasts (and non-bacteria) were obtained and provide rarefaction curves. Same for metagenomes. Line 202. Is the dataset also normalized based on the number of the 16S rRNA gene present in different taxa/ASVs? Line 248 repetition of "dried out" Line 240. The authors should briefly describe the condition of the three sites, and, if it is possible, also include C and other nutrient contents. Lines 268-269. I suggest keeping the definition of the gradient as "desiccation" and not temporal. What do you mean by "Temporal changes"? if all the plants and soil were collected on the same day, the main changes observed in the rhizosphere/soil across the three sites are due to the "desiccation gradient". Moreover, the same desiccation is correlated/explained by time, so only one of these factors can be sued to describe/explain the differences observed. Line 306. Remove highlight from "Glycomyces". Lines 327-333. Specify the type of genes included. Are all those differentially distributed across samples, or only those related to PGP/beneficial traits? Line 436. Why do the mechanisms describe here can be defined as new? Several works showed how the rhizosphere tends to select core functional microbiome, as well as microbes enriched in PGP functions/traits that support plant growth. If this statement refers only to the archaea/bacteria ratio, please clarify it. Figure 1. specify from amplicon dataset as done in Figure 2. Figure 4A. maybe it can be clustered based on the distribution of metabolism across MAGs or on the distribution of MAGs in the three sites. It is difficult to follow the pattern described. Figure 5. Correlation with chemistry data already published could additionally explain the pattern observed, especially trophic behaviours and C-metabolisms. Structural equation modelling (SEM) could be useful to explain the pattern observed, as well as it could be interesting to explore the correlation between microbes involved in different carbon and nitrogen cycling at different sites (e.g., pathway and corresponding percentage of genomes encoding the respective genes by using METABOLIC doi:10.1186/s40168-021-01213-8). Table S1. What does star (*) means? From the caption, it is not clear. I suppose that pools were performed for bulk soil samples. However, from the methods, it is not clear if this was done for both amplicon and metagenome sequencing.
Tables S2 and S3. Please specify that these tables refer to the amplicon datasets. What does star (*) means? From the caption, it is not clear. Table S5. I suppose this comes from the rhizosphere. Please specify. I also suggest, since three replicates were analyzed, adding the standard deviation to the relative abundance reported. If it is not possible, specify that the three metagenomes were pooled/merged to obtain MAGs; if it is the case how is relative abundance calculated? How did you compare? Which statistical analysis was applied? Supplementary Figure S1. It could be interesting to present another set of panels with the same results from metagenomes. As well as add rarefaction curves for amplicon and metagenomes approaches, at least based on 16S rRNA diversity in the rhizosphere and soil across the three-time points. Supplementary Figure S3. What was used to calculate Shannon diversity? Did you use the 16S rRNA genes, MAGs, or functional genes from the metagenome approach? Please specify. Moreover, why are shown four black dots per box plot if the rhizosphere samples are three per time-point? See NMDS and Table S1. Supplementary Figure S4. Are A and C referring to the compositional diversity of community based on the 16S rRNA gene from metagenome/MAGs? Which taxonomic level was considered? Which functions were included in B and D? Please specify. Supplementary Figure S5. From which compartment the MAGs showed were obtained? Rhizosphere and/or soil? Dear Dr. Tomislav Cernava: Thank you for submitting your manuscript to mSystems. The reviewers have now assessed your work and recommend it for publication after a number of issues have been addressed.
For instance, please check metagenomic data for eukaryotic reads to see whether fungal communities may play a role in this ecosystem. The reviewers also recommend deepening the functional analysis, taking biochemical data such as salinity into account. Such data could also help to quantify what is meant by "extreme" desiccation.
Below you will find instructions from the mSystems editorial office and comments generated during the review. Sincerely,

Karoline Faust
Editor, mSystems  Dear Prof. Faust, Thank you for the opportunity to revise our manuscript titled "Function-based rhizosphere assembly along a gradient of desiccation in the former Aral Sea".
We have carefully considered all of the highly constructive comments provided by the reviewers and revised our manuscript accordingly. Thanks also for comments you pointed out. We analyzed metagenomic data for eukaryotic reads to see whether fungal communities may play a role in this ecosystem. Here, we have an answer -they seem to be less responsive to the parameter along the gradient. We decided to add this in the discussion section but not to the manuscript because this was not the scope of our study. Data are shown in the rebuttal letter. In addition, we have performed a detailed functional analysis, which was enclosed.
We appreciate all helpful comments and hope that the new version of our manuscript merits to be published in mSystems.

Reviewer #1 (Comments for the Author):
In the manuscript "Function-based rhizosphere assembly along a gradient of desiccation in the former Aral Sea", as the authors indicated, these results confirm that along the desiccation gradient, a significant change in the rhizosphere microbiota were observed in the rhizosphere microbiota of native pioneer plants. The results provide evidence that rhizosphere assembly by co-filtering specific taxa with distinct traits is a mechanism, which allows plants to thrive under extreme conditions. Here are some suggestions about this manuscript.
 Thank you for your constructive comments. We have addressed your comments point-bypoint as you will see below. They have certainly helped us to improve the manuscript.
1. Clearly explain the significant changes in the rhizosphere microbiota of native pioneer plants across a gradient of desiccation (5, 10, and 40 years) were obtained in the abstract.
 The changes were reflected by differences in the archaea-bacteria ratio and the replacement of halophilic bacteria by typical plant-associated bacteria with specific plantbeneficial biosynthetic pathways. We revised the sentence in the Abstract in line 37 as follows: "Along the desiccation gradient, we observed a significant change in the rhizosphere microbiota, which was reflected by i) a decreasing archaea-bacteria ratio, ii) replacement of halophilic archaea by specific plant-associated bacteria i.e., Alphaproteobacteria and Actinobacteria, and iii) an adaptation of specific, potentially plant-beneficial biosynthetic pathways." 2.Line 32-34, "The rhizosphere effect was shown by significantly higher abundances but less diversity in the rhizosphere compared to bulk soil in all samples." Do bacterial and archaeal communities have the same alteration trend?
 Thank you for pointing this out. Yes, the rhizosphere effect in terms of the decrease of diversity, was consistently shown for the bacterial and archaeal communities (except for the archaeal abundance that is only higher in rhizosphere soil in comparison to bulk soil in the area that dried out 40 years ago).
3.Why bacterial and archaeal communities were investigated rather than fungal communities?
 Indeed, the fungal community is an interesting topic. Currently there are only limited studies addressing microbial communities in the Aral Sea basin. We focused on bacteria due to their relatively high abundance in plant-associated habitats. We hypothesized that they would also play important roles in this extreme environment. Archaea that also commonly colonize extreme environments and we therefore hypothesizes that they might have implications for supporting host plants in this environment.
We performed additional analyses to investigate the impacts of the desiccation gradient on the fungal community structure based on shot-read metagenome sequencing. Interestingly, the fungal community structure was less responsive to the gradient of desiccation, but two major clusters were found (R 2 =37.9%, P=0.069, Figure 1). Due to the microbial dynamics in this environment, findings from this study provide a solid basis for larger, follow-up studies that include other members of the plant holobiont, e.g. fungi that were not in the scope of this study.  We have included a reference in the text.
5.Line 126-128, "We collected bulk soil and rhizosphere samples (three biological replicatesapprox. 5 g per biological replicate) of the plant Suaeda acuminata (C.A.Mey.) Moq. in the dried-out basin and near the west shoreline of the South Aral Sea". Overall, my concern is why Suaeda acuminata was select?
 Suaeda acuminata was chosen because it is the first pioneer plant colonizing the driedout Aral Sea basin, and the only one present along the gradient. Hence, this allowed us to compare its prokaryotic community structures along the natural revegetation stages.
6.Line 296, delete an "in".  Thank you for the comment. We agree that the details are missing for the figure legend.
To avoid reader's confusion, we have revised the figure legend as follows: Figure 1. Sampling site, bacterial and archaeal abundance, diversity and community structure in bulk soil and the rhizosphere of Suaeda acuminata. Different sampling sites represent the gradient of salinity (high, medium, and low salinity) and natural revegetation events in the Aral Sea basin where bulk soil and rhizosphere samples were collected (A). Geochemistry, mineralogy, and the number of visible plants species were previously described (Jiang et al., 2020). Bacterial and archaeal 16S rRNA gene copy numbers were calculated by using qPCR (B, C, and D). The diversity of bacterial (C) and archaeal (D) communities was estimated using the Shannon index in bulk and rhizosphere soils within the analyzed desiccation gradient (5 -40 years).
 Thank you for pointing this out. We have revised the figure and clearly explained the gradient of salinity in the figure legend.
Reviewer #2 (Comments for the Author): The manuscript mSystems00739-22 by Wicaksono and coauthors reports an investigation of the compositional and functional diversity and quantification of prokaryotes (bacteria and archaea) associated with the rhizosphere of native pioneer halophytic Suaeda acuminata along a desiccation gradient in the former Aral Sea. Metagenome and amplicon sequences approach, along with qPCR, were applied to 12 samples (9 rhizospheres and 3 soils) across three sites exposed to desiccation for 5, 10 and 40 years. Different bacterial microbiomes were found in the rhizosphere and soil, with different structures and assemblies among the sites, due to the combination of plant co-filtering and environmental conditions of sites (desiccation, salt concentration, toxin, etc.). Notably, along the desiccation gradient, the authors showed that the rhizosphere microbial communities had a decreasing archaeabacteria ratio, a replacement of halophilic archaea by certain bacteria, and an adaptation of specific beneficial microbial functions, such as carbon cycling and fixation, methane and nitrogen metabolism, and production of osmoprotectants, which could support plants to thrive under extreme conditions.
Overall, the manuscript is well written, the results are clearly presented, and the conclusions are well supported.
 Thank you for the positive comments. We appreciate the constructive suggestions. We have addressed all of your comments and have carefully edited the manuscript. We believe the revised version has improved.
Below are some minor criticisms and my comments/suggestions: 1. Line 33. Which pioneer plant? Maybe it can be specified from the beginning. Are all the collected plants the same species? Is this evaluated?
 We agree that the name of plant needs to be specified in the beginning. We added this information in line 31 as follows: "Here we investigated the rhizosphere microbiota of the native pioneer plant Suaeda acuminata (C.A.Mey.) Moq, in comparison to bulk soil across a gradient of desiccation (5, 10, and 40 years) by metagenome and amplicon sequencing combined with qPCR analyses." Yes, they are from the same species. We have identified the plant species according to its specific morphology.
2. Line 35. Why is the site with 5 years of desiccation considered the most extreme? Not really get this sentence. I suppose that at this site the salt concentration is the highest. I suggest reporting at least this info related to the three sites also in the abstract.
 Yes, this is true. The area that dried out 5 years ago is considered the most extreme due to high salinity which limits organisms to grow. We added this information in the abstract to clarify our sentence.
3. Line 42. Are these MAGs coming only from the rhizosphere?
 The MAGs collection was also constructed from bulk soil metagenomes. We constructed a non-redundant genome collection using dRep (Olm et al., 2017). This information was missing in the previous MS version. We have added these information in line 223 as follows . The authors showed that the root system represents a microbial density and competition hotspot ruled out by a dual selection process: to colonize the plant-associated niches microorganisms must (1) possess the capacity to improve the fitness and survival of the plant (plant selection of beneficial microbes, PGP bacteria) and be able (2) to compete successfully against other microorganisms (microbial competition). It will be interesting to explore if this competition is also present in salty/desiccation soils and how this occurs along the desiccation gradient.
 This is an interesting point. Evidence that microbes possess the capacity to improve the fitness and survival of the plant were shown based on genome centric analysis. We observed that many of the recovered MAGs harboured genes related to biochemical pathways that may improve plant growth (line 380) also protection against abiotic factors i.e., spermidine and betaine transport systems. We also extensively searched genes related to plant growth promotion and protection against abiotic factors in our metagenome dataset (see list of the genes below). The abundance profiles of these genes changed within the gradient of desiccation (line 338). For example, a high abundance of genes associated with osmoprotectant transporters increased along the desiccation gradient as well as genes involved in detoxification of heavy metals. Due the importance of referred paper regarding the recruitment of microbes with functional capacity to improve plant growth in dessert environment, we added this reference into the manuscript (line 461).
"A recent study from a hyper arid environment also suggested that plant may have coevolved with specific bacterial taxa that possess the capacity to improve the fitness and  ABC.SP.A; putative spermidine/putrescine transport system ATP-binding protein K02053 ABC.SP.P; putative spermidine/putrescine transport system permease protein K02054 ABC.SP.P1; putative spermidine/putrescine transport system permease protein K02055 ABC.SP.S; putative spermidine/putrescine transport system substrate-binding protein We additionally searched for genes associated with antibiotic biosynthesis and calculated their total abundance (RPKM, Figure 1). However, we did not find significant differences between the sampling sites (Kruskal-Wallis -P-value = 0.429).  We agree with the reviewer. This aspect was discussed in line 525 -535.
6. Line 130. How did you collect 5 g of rhizosphere? How many plants were used for each replicate? Is this species the main abundance? How is it distributed along the desiccation gradient?
 From each area, samples were taken from three independent biological replicates (from three different S. acuminata populations), each consisting of combined roots of three individual plants to obtain at least 5 g material per biological replicate. Rhizosphere samples were collected by light shaking of the roots to remove loosely attached soil before they were further treated in the laboratory as described below.
To clarify our sampling, strategy, we revised our method as follows (line 121  We agree this passage is not clear. We only used a fraction of the total samples for the DNA extraction. We revised our sentence in line 136 as follows: "Fractions of 2 mL of the resulting suspensions were centrifuged at 16,000 x g and 4 °C with a Sorvall RC-5B Refrigerated Superspeed Centrifuge (DuPont Instruments; USA) for 20 min." The weight of the pellet was approx. 0.1 g. We added this information to the text.
9. Lines 156-157. How were qPCR results normalized? Based on the taxonomy obtained the different copy numbers of 16S rRNA of bacterial and archaea communities could be retrieved across the three sites.
 The qPCR data was normalized according to the weight of the samples. We added information on how the copy numbers were computed as below: "Serial dilutions of a standard containing a defined 16S rRNA gene copy number of Bacillus sp. and Haloferax denitrificans were used for the calculation of bacterial and archaeal gene copy numbers in different samples, respectively. The copy numbers of bacterial and archaeal 16S rRNA genes were normalized according to the weight of the samples." 10. Line 179. Why Silva 128? A more recent version (138) is available. Is the classifier trained with the primer used? Please specify how many chloroplasts (and non-bacteria) were obtained and provide rarefaction curves. Same for metagenomes.
 This was a mistake, we used Silva 132, however not Silva 138. We additionally performed a taxonomic assignment using the more recent version of Silva and observed that general statistical patterns i.e., beta diversity are congruent between the "older" and "most recent" Silva databases. Hence, we decided to keep it as it was. 13. Lines 268-269. I suggest keeping the definition of the gradient as "desiccation" and not temporal. What do you mean by "Temporal changes"? if all the plants and soil were collected on the same day, the main changes observed in the rhizosphere/soil across the three sites are due to the "desiccation gradient". Moreover, the same desiccation is correlated/explained by time, so only one of these factors can be sued to describe/explain the differences observed.
 We agree with the reviewer. We removed "temporal" throughout the MS.
 It is now removed.  We removed "novel" from the sentence.
18. Figure 1. specify from amplicon dataset as done in Figure 2.
 Thank you for pointing this out. The figure legend is now revised.
19. Figure 4A. maybe it can be clustered based on the distribution of metabolism across MAGs or on the distribution of MAGs in the three sites. It is difficult to follow the pattern described.
 We generated a new figure and included a bar plot to show MAG abundance distribution in the three sites.  Table S5). Principal coordinate analysis (PCoA) of MAG clusters is based on genes encoding transporter protein counts in the genomes (C). MAGs belonging to Halomonas are indicated with arrows (C).
20. Figure 5. Correlation with chemistry data already published could additionally explain the pattern observed, especially trophic behaviours and C-metabolisms. Structural equation modelling (SEM) could be useful to explain the pattern observed, as well as it could be interesting to explore the correlation between microbes involved in different carbon and nitrogen cycling at different sites (e.g., pathway and corresponding percentage of genomes encoding the respective genes by using METABOLIC doi:10.1186/s40168-021-01213-8).
 This is an interesting point. However, such an analysis would need more data points. We are planning to perform a more comprehensive follow-up study and combine it with a cultureomics approach to reveal microbial functions involved in plant growth promotion and abiotic stress including carbon and nitrogen cycling.
21.  Figure S1. It could be interesting to present another set of panels with the same results from metagenomes. As well as add rarefaction curves for amplicon and metagenomes approaches, at least based on 16S rRNA diversity in the rhizosphere and soil across the three-time points.
 We added a bar plot that shows the relative abundance of bacteria and archaea of the total prokaryotic reads as determined using shotgun metagenome sequencing and mentioned it in the main text (Supplementary Figure S2B) as follows (line 285) "Comparable to the qPCR results, the ratio between the archaeal and the bacterial relative abundance as determined using amplicon sequencing gradually decreased in the rhizosphere along the gradient of desiccation ( Supplementary Fig. S2A). A similar pattern was observed with the metagenome dataset ( Supplementary Fig. S2B)." Supplementary Figure S1. Relative abundance between bacteria and archaea as determined using amplicon sequencing (A) and shotgun metagenome sequencing.
We also added rarefaction curves for the amplicon analysis as suggested ( Supplementary   Fig. S2).
Rarefractions curves indicated that our sequencing depth was sufficient to capture overall bacterial and archaeal diversity.  Table S1.

Supplementary
 The Shannon index was calculated using observed number of species and their abundances that were generated using the shotgun metagenomic sequencing approach. We clarified this approach in line 264 as follows: "The Shannon diversity index based on shotgun metagenomic sequencing approach also indicated a congruent result (P=0.429 and P=0.732, respectively; Supplementary Fig. S4)." The fourth dot is mean standard deviation. We decided to remove the dot to avoid reader's confusion. Figure S4. Are A and C referring to the compositional diversity of community based on the 16S rRNA gene from metagenome/MAGs? Which taxonomic level was considered? Which functions were included in B and D? Please specify.

Supplementary
Supplementary Figure S5. From which compartment the MAGs showed were obtained?
Rhizosphere and/or soil?
 Figure S4A and B refer to the community structure based on 16S rRNA amplicon sequencing whereas C and D refer to gene profiles based on the shotgun metagenome sequencing. We revised the figure legends (which is now Supplementary Figure 5  I am pleased to inform you that your manuscript has been accepted, and I am forwarding it to the ASM Journals Department for publication. For your reference, ASM Journals' address is given below. Before it can be scheduled for publication, your manuscript will be checked by the mSystems production staff to make sure that all elements meet the technical requirements for publication. They will contact you if anything needs to be revised before copyediting and production can begin. Otherwise, you will be notified when your proofs are ready to be viewed.
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